Geographic Information and Communication Technologies for Supporting Smallholder Agriculture and Climate Resilience
Abstract
:1. Introduction
- i.
- What are the key challenges that AGI initiatives aim to address?
- ii.
- What technological approaches have been adopted to provide AGI to smallholder farmers?
- iii.
- Who are the target users of AGI initiatives and how have initiatives been adopted?
- iv.
- What are the factors promoting or limiting the success of AGI initiatives?
2. Geographic Information in Agriculture
2.1. Information Needs of Smallholders
2.1.1. Information Availability
2.1.2. Information Accessibility
2.1.3. Information Applicability
3. Methodology
4. Results
4.1. AGI Initiatives
4.1.1. Agro-Climatic Challenges Being Addressed
4.1.2. Technological Provisioning to Smallholder Farmers
4.1.3. Adoption of Initiatives
4.2. Factors Promoting or Limiting AGI Success
4.2.1. Farmer Capacity
4.2.2. Approach
4.2.3. Technological
4.2.4. Organisational
5. Future Potential of AGI
5.1. Geographical Targeting
5.2. Types of Information and Information Technologies
5.3. Independent Assessment of Initiatives
5.4. Inclusivity for Multi-Level Stakeholder Communication
6. Summary
Author Contributions
Funding
Conflicts of Interest
References
- Sylvester, G. Success Stories on Information and Communication Technologies for Agriculture and Rural Development, 2nd ed.; Food and Agriculture Organization of the United Nations: Rome, Italy, 2015; Available online: http://www.fao.org/3/a-i4622e.pdf (accessed on 8 May 2017).
- Samberg, L.H.; Gerber, J.S.; Ramankutty, N.; Herrero, M.; West, P.C. Subnational distribution of average farm size and smallholder contributions to global food production. Environ. Res. Lett. 2016, 11, 124010. [Google Scholar] [CrossRef] [Green Version]
- Swanson, B. Global Review of Good Agricultural Extension and Advisory Service Practice; Food and Agriculture Organization of the United Nations: Rome, Italy, 2008. [Google Scholar]
- Knox, J.; Hess, T.; Daccache, A.; Wheeler, T. Climate change impacts on crop productivity in Africa and South Asia. Environ. Res. Lett. 2012, 7, 034032. [Google Scholar] [CrossRef] [Green Version]
- Coumou, D.; Rahmstorf, S. A decade of weather extremes. Nat. Clim. Chang. 2012, 2, 491–496. [Google Scholar] [CrossRef]
- Trenberth, K.E. Changes in precipitation with climate change. Clim. Res. 2011, 47, 123–138. [Google Scholar] [CrossRef] [Green Version]
- Lobell, D.; Schlenker, W.; Costa-Roberts, J. Climate trends and global crop production since 1980. Science 2011, 333, 616–620. [Google Scholar] [CrossRef] [PubMed]
- Hochman, Z.; Horan, H.; Reddy, D.R.; Sreenivas, G.; Tallapragada, C.; Adusumilli, R.; Gaydon, D.S.; Laing, A.; Kokic, P.; Singh, K.K.; et al. Smallholder farmers managing climate risk in India: 2. Is it climate-smart? Agric. Syst. 2017, 151, 61–72. [Google Scholar] [CrossRef]
- Thornton, P.K.; Lipper, L. How Does Climate Change Alter Agricultural Strategies to Support Food Security? IFPRI Discussion Paper 01340; IFPRI: Washington, DC, USA, 2013. [Google Scholar]
- Dow, K.; Berkhout, F.; Preston, B.L.; Klein, R.J.; Midgley, G.; Shaw, M.R. Limits to adaptation. Nat. Clim. Chang. 2013, 3, 305–307. [Google Scholar] [CrossRef]
- Jayaraman, T.; Murari, K. Climate change and agriculture: Future trends and implications for India. Rev. Agrar. Stud. 2014, 4, 1–49. [Google Scholar]
- Barrett, C.B.; Reardon, T.; Webb, P. Nonfarm income diversification and household livelihood strategies in rural Africa: Concepts, dynamics, and policy implications. Food Policy 2001, 26, 315–331. [Google Scholar] [CrossRef]
- Jayne, T.S.; Mather, D.; Mghenyi, E. Principal challenges confronting smallholder agriculture in Sub-Saharan Africa. World Dev. 2010, 38, 1384–1398. [Google Scholar] [CrossRef]
- Tittonell, P.; Giller, K.E. When yield gaps are poverty traps: The paradigm of ecological intensification in African smallholder agriculture. Field Crops Res. 2013, 143, 76–90. [Google Scholar] [CrossRef]
- Fisher, M.; Carr, E.R. The influence of gendered roles and responsibilities on the adoption of technologies that mitigate drought risk: The case of drought-tolerant maize seed in eastern Uganda. Glob. Environ. Chang. 2015, 35, 82–92. [Google Scholar] [CrossRef] [Green Version]
- Carter, M.R.; Little, P.D.; Mogues, T.; Negatu, W. Poverty traps and natural disasters in Ethiopia and Honduras. World Dev. 2007, 35, 835–856. [Google Scholar] [CrossRef]
- Goodchild, M.F. Citizens as sensors: The world of volunteered geography. GeoJournal 2007, 69, 211–221. [Google Scholar] [CrossRef]
- Elwood, S. Geographic information science: Emerging research on the societal implications of the geospatial web. Prog. Hum. Geogr. 2010, 34, 349–357. [Google Scholar] [CrossRef]
- Kuhn, W. Geospatial Semantics: Why, of What, and How. In Journal on Data Semantics III. Lecture Notes in Computer Science; Spaccapietra, S., Zimányi, E., Eds.; Springer: Berlin, Germany, 2005; Volume 3534. [Google Scholar]
- Longley, P.A.; Goodchild, M.F.; Maguire, D.J.; Rhind, D.W. Geographic Information Systems and Science, 2nd ed.; John Wiley and Sons Ltd.: Chichester, UK, 2006. [Google Scholar]
- Open Geospatial Consortium (OGC). Glossary of Terms—G. 2017. Available online: http://www.opengeospatial.org/ogc/glossary/g (accessed on 5 May 2017).
- Craglia, M.; Ostermann, F.; Spinsanti, L. Digital Earth from vision to practice: Making sense of citizen-generated content. Int. J. Digit. Earth 2012, 5, 398–416. [Google Scholar] [CrossRef]
- Benson, A.; Jafry, T. The state of agricultural extension: An overview and new caveats for the future. J. Agric. Educ. Ext. 2013, 19, 381–393. [Google Scholar] [CrossRef]
- Anderson, J.R.; Feder, G. Agricultural extension: Good intentions and hard realities. World Bank Res. Obs. 2004, 19, 41–60. [Google Scholar] [CrossRef]
- Taylor, M.; McGregor, A.; Dawson, B. Vulnerability of Pacific Island Agriculture and Forestry to Climate Change; Pacific Community: New Caledonia, 2016; Available online: https://spccfpstore1.blob.core.windows.net/digitallibrary-docs/files/6f/6fdef19c8085874a0406d7e1f64897bd.pdf?sv=2015-12-11andsr=bandsig=qUFufXOhh7WrD9g5SQuNcg89y1d4QUHTmUiUPqK0hEo%3Dandse=2018-05-20T04%3A14%3A47Zandsp=randrscc=public%2C%20max-age%3D864000%2C%20max-stale%3D86400andrsct=application%2Fpdfandrscd=inline%3B%20filename%3D%22Vulnerability_Pacific_agriculture_climate_change.pdf%22 (accessed on 12 December 2017).
- Duncan, J.M.; Tompkins, E.L.; Dash, J.; Tripathy, B. Resilience to hazards: Rice farmers in the Mahanadi Delta, India. Ecol. Soc. 2017, 22, 3. [Google Scholar] [CrossRef]
- Mittal, S. Role of Mobile Phone-enabled Climate Information Services in Gender-inclusive Agriculture. Gend. Technol. Dev. 2016, 20, 200–217. [Google Scholar] [CrossRef] [Green Version]
- Glendenning, C.J.; Babu, S.; Asenso-Okyere, K. Review of Agricultural Extension in India. IFPRI Discussion Paper 01048. International Food Policy Research Institute, 2010. Available online: http://cdm15738.contentdm.oclc.org/utils/getfile/collection/p15738coll2/id/7280/filename/7281.pdf (accessed on 16 June 2017).
- Balaghi, R.; Badjeck, M.C.; Bakari, D.; De Pauw, E.; De Wit, A.; Defourny, P.; Donato, S.; Gommes, R.; Jlibene, M.; Ravelo, A.C.; et al. Managing Climatic Risks for Enhanced Food Security: Key Information Capabilities. Procedia Environ. Sci. 2010, 1, 313–323. [Google Scholar] [CrossRef]
- Yonazi, E.; Kelly, T.; Halewood, N.; Blackman, C. eTransform Africa 2012: The Transformational Use of Information and Communication Technologies in Africa; World Bank, African Development Bank and African Union: Washington, DC, USA; Tunis, Tunisia, 2012. [Google Scholar]
- Ballantyne, P. Accessing, sharing and communicating agricultural information for development: Emerging trends and issues. Inf. Dev. 2009, 25, 260–271. [Google Scholar] [CrossRef]
- Baumüller, H. The little we know: An exploratory literature review on the utility of mobile phone-enabled services for smallholder farmers. J. Int. Dev. 2018, 30, 134–154. [Google Scholar] [CrossRef]
- Food and Agriculture Organization of the United Nations (FAO). e-Agriculture 10 Year Review Report; Food and Agriculture Organization of the United Nations: Rome, Italy, 2015. [Google Scholar]
- World Bank. ICT in Agriculture: Connecting Smallholders to Knowledge, Networks, and Institutions; World Bank: Washington, DC, USA, 2011. [Google Scholar]
- Duncombe, R. Mobile phones for agricultural and rural development: A literature review and suggestions for future research. Eur. J. Dev. Res. 2016, 28, 213–235. [Google Scholar] [CrossRef]
- Wang, J.; Chen, J.; Ju, W.; Li, M. IA-SDSS: A GIS-based land use decision support system with consideration of carbon sequestration. Environ. Model. Softw. 2010, 25, 539–553. [Google Scholar] [CrossRef]
- Adenle, A.A.; Azadi, H.; Arbiol, J. Global assessment of technological innovation for climate change adaptation and mitigation in developing world. J. Environ. Manag. 2015, 161, 261–275. [Google Scholar] [CrossRef]
- Kroschel, J.; Sporleder, M.; Tonnang, H.E.Z.; Juarez, H.; Carhuapoma, P.; Gonzales, J.C.; Simon, R. Predicting climate-change-caused changes in global temperature on potato tuber moth Phthorimaea operculella (Zeller) distribution and abundance using phenology modeling and GIS mapping. Agric. For. Meteorol. 2013, 170, 228–241. [Google Scholar] [CrossRef]
- Aubert, B.A.; Schroeder, A.; Grimaudo, J. IT as enabler of sustainable farming: An empirical analysis of farmers’ adoption decision of precision agriculture technology. Decis. Support Syst. 2012, 54, 510–520. [Google Scholar] [CrossRef]
- Bongiovanni, R.; Lowenberg-DeBoer, J. Precision agriculture and sustainability. Precis. Agric. 2004, 5, 359–387. [Google Scholar] [CrossRef]
- Zhang, N.; Runquist, E.; Schrock, M.; Havlin, J.; Kluitenburg, G.; Redulla, C. Making GIS a versatile analytical tool for research in precision farming. Comput. Electron. Agric. 1999, 22, 221–223. [Google Scholar] [CrossRef]
- Meier, P. Crisis mapping in action: How open source software and global volunteer networks are changing the world, one map at a time. J. Map Geogr. Libr. 2012, 8, 89–100. [Google Scholar] [CrossRef]
- Haworth, B.T.; Bruce, E.; Whittaker, J.; Read, R. The good, the bad, and the uncertain: Contributions of volunteered geographic information to community disaster resilience. Front. Earth Sci. 2018, 6, 183. [Google Scholar] [CrossRef]
- FAO. Climate-Smart Agriculture Sourcebook; FAO: Rome, Italy, 2013; Available online: http://www.fao.org/docrep/018/i3325e/i3325e00.htm (accessed on 4 December 2018).
- Thornton, P.K.; Aggarwal, P.; Parsons, D. Editorial: Prioritising climate-smart agricultural interventions at different scales. Agric. Syst. 2017, 151, 149–152. [Google Scholar] [CrossRef]
- World Bank. Enhancing Agricultural Innovation: How to Go beyond the Strengthening of Research Systems; World Bank: Washington, DC, USA, 2007; Available online: http://siteresources.worldbank.org/INTARD/Resources/EnhancingAgInnovationebook.pdf (accessed on 9 May 2017).
- Obayelu, A.; Ogunlade, I. Analysis of the uses of information communication technology (ICT) for gender empowerment and sustainable poverty alleviation in Nigeria. Int. J. Educ. Dev. Using ICT 2006, 2, 45–69. [Google Scholar]
- Dang, H.L.; Li, E.; Bruwer, J.; Nuberg, I. Farmers’ perceptions of climate variability and barriers to adaptation: Lessons learned from an exploratory study in Vietnam. Mitig. Adapt. Strateg. Glob. Chang. 2014, 19, 531–548. [Google Scholar] [CrossRef]
- Hudson, S.; Krogman, N.; Beckie, M. Social practices of knowledge mobilization for sustainable food production: Nutrition gardening and fish farming in the Kolli hills of India. Food Secur. 2016, 8, 523–533. [Google Scholar] [CrossRef]
- Kumar, K.R.; Nain, M.S.; Singh, R.; Bana, R.S. Analysis of farmers’ communication network and factors of knowledge regarding agro meteorological parameters. Indian J. Agric. Sci. 2015, 85, 1592–1596. [Google Scholar]
- Palmer, T.; Pshenichnaya, N. Tigo Kilimo Impact Evaluation; GSMA: London, UK, 2015; Available online: http://www.gsma.com/mobilefordevelopment/programme/magri/assessing-the-impact-of-tigo-kilimo (accessed on 15 August 2017).
- Munyna, H. Application of ICTs in Africa’s agricultural sector: A gender perspective. In Gender and the information revolution in Africa; Rathgeber, E.M., Adera, E.O., Eds.; International Development Research Centre: Ottawa, ON, Canada, 2000; pp. 85–124. [Google Scholar]
- Gandhi, R.; Veeraraghavan, R.; Toyama, K.; Ramprasad, V. Digital Green: Participatory video for agricultural extension. In Proceedings of the 2007 International Conference on Information and Communication Technologies and Development, Bangalore, India, 15–16 December 2007. [Google Scholar]
- Rola, A.C.; Quizon, J.B.; Jamias, S.B. Do Farmer Field School Graduates Retain and Share What They Learn? An Investigation in Iloilo, Philippines. J. Int. Agric. Ext. Educ. 2002, 5, 65–75. [Google Scholar] [CrossRef]
- Walsham, G.; Sahay, S. Research on information systems in developing countries: Current landscape and future prospects. Inf. Technol. Dev. 2006, 12, 7–24. [Google Scholar] [CrossRef]
- Metcalfe, M.; Joham, C. The “ear” and “eye” digital divide. In Organizational Information Systems in the Context of Globalization; Korpela, M., Montealegre, R., Poulymenakou, A., Eds.; Springer: Boston, MA, USA, 2003; pp. 419–434. [Google Scholar]
- Livoreil, B.; Glanville, J.; Haddaway, N.R.; Bayliss, H.; Bethel, A.; de la Chapelle, F.F.; Robalino, S.; Savilaakso, S.; Zhou, W.; Petrokofsky, G.; et al. Systematic searching for environmental evidence using multiple tools and sources. Environ. Evid. 2017, 6, 23. [Google Scholar] [CrossRef]
- FAO. Enhancing Agriculture Monitoring System Based on Geospatial Technology in Afghanistan. 2016. Available online: http://www.fao.org/3/a-i5569e.pdf (accessed on 15 August 2017).
- Groupe Spéciale Mobile Association (GSMA). Case Study: Airtel Kilimo, Kenya; GSMA: London, UK, 2015; Available online: http://www.gsma.com/mobilefordevelopment/wp-content/uploads/2015/02/GSMA_Case_Airtel_FinalProof02.pdf (accessed on 15 August 2017).
- Cole, S.; Fernando, A.N. Mobile’izing Agricultural Advice: Technology Adoption, Diffusion and Sustainability. Harvard Business School Working Paper. Cambridge, UK, April 2016. Available online: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2179008anddownload=yes (accessed on 10 October 2017).
- Girvetz, E.H.; Zganjar, C.; Raber, G.T.; Maurer, E.P.; Kareiva, P.; Lawler, J.L. Applied Climate-Change Analysis: The Climate Wizard Tool. PLoS ONE 2009, 4, e8320. [Google Scholar] [CrossRef] [PubMed]
- Bruce, T.J.A. The CROPROTECT project and wider opportunities to improve farm productivity through web- based knowledge exchange. Food Energy Secur. 2016, 5, 89–96. [Google Scholar] [CrossRef] [PubMed]
- Gandhi, R. Case Study 1: Digital Green: Leveraging social networks for agricultural extension. In Success Stories on Information and Communication Technologies for Agriculture and Rural Development, 2nd ed.; Sylvester, G., Ed.; Food and Agriculture Organization of the United Nations: Rome, Italy, 2015; Available online: http://www.fao.org/3/a-i4622e.pdf (accessed on 8 May 2017).
- Trogo, R.; Ebardaloza, J.B.; Sabido, D.J.; Bagtasa, G.; Tongson, E.; Balderama, O. SMS-based Smarter Agriculture Decision Support System for Yellow Corn Farmers in Isabela. In Proceedings of the IEEE Canada International Humanitarian Technology Conference (Ihtc2015), Ottawa, ON, Canada, 31 May–4 June 2015. [Google Scholar]
- GSMA. Farmforce; GSMA: London, UK, 2013; Available online: http://www.gsma.com/mobilefordevelopment/programme/magri/farmforce (accessed on 16 October 2017).
- FAO. Monitoring of Rice Crop Using Satellite Remote Sensing and GIS Technologies in Northern and Eastern Afghanistan. 2016. Available online: http://www.fao.org/3/a-i6146e.pdf (accessed on 22 August 2017).
- Darabian, N. Case Study IFFCO Kisan Agriculture App: Evolution to Data Driven Services in Agriculture. GSMA, London. 2016. Available online: http://www.gsma.com/mobilefordevelopment/programme/magri/iffco-kisan-agricultural-app-evolution-to-data-driven-services-in-agriculture (accessed on 15 August 2017).
- Masinde, M.; Bagula, A.; Muthama, N. Implementation Roadmap for Downscaling Drought Forecasts in Mbeere Using Itiki. In Proceedings of the 2013 Itu Kaleidoscope Academic Conference: Building Sustainable Communities (K-2013), Kyoto, Japan, 22–24 April 2013; pp. 63–70. [Google Scholar]
- Ignitia. Ignitia, Tropical Weather Forecasting. 2017. Available online: www.ignitia.se (accessed on 16 June 2017).
- United Nations Development Program (UNDP). Using SMS Texts to Provide Weather Forecasts for Small Farmers in West Africa. December 2015. Available online: http://www.undp.org/content/undp/en/home/presscenter/pressreleases/2015/12/22/using-sms-texts-to-provide-weather-forecasts-for-small-farmers-in-west-africa.html (accessed on 16 June 2017).
- Jayalaxmi Agro Tech. Welcome to Jayalaxmi Agro Tech. 2014. Available online: http://www.jayalaxmiagrotech.com/ (accessed on 21 August 2017).
- Wenkel, K.O.; Berg, M.; Mirschel, W.; Wieland, R.; Nendel, C.; Kostner, B. LandCaRe DSS—An interactive decision support system for climate change impact assessment and the analysis of potential agricultural land use adaptation strategies. J. Environ. Manag. 2013, 127, S168–S183. [Google Scholar] [CrossRef] [PubMed]
- Ogodo, O. African Farmers Get Geospatial Info on Their Phones. SciDevNet, 24 April 2009. Available online: http://www.scidev.net/global/farming/news/african-farmers-get-geospatial-info-on-their-phone.html (accessed on 19 August 2017).
- Laraki, J. Case Study 6: Mobile market information service: A pilot project of ICT use for smallholder farmers in Papua New Guinea. In Success Stories on Information and Communication Technologies for Agriculture and Rural Development, 2nd ed.; Sylvester, G., Ed.; Food and Agriculture Organization of the United Nations: Rome, Italy, 2015; Available online: http://www.fao.org/3/a-i4622e.pdf (accessed on 8 May 2017).
- Reichel, C.; Frömming, U.U. Participatory mapping of local disaster risk reduction knowledge: An example from Switzerland. Int. J. Disaster Risk Sci. 2014, 5, 41–54. [Google Scholar] [CrossRef]
- Slawson, N. Radio Monsoon attempts to ensure safety reigns among fisherman in south India. The Guardian, 24 April 2017. Available online: https://www.theguardian.com/global-development/2017/apr/24/radio-monsoon-safety-fishermen-south-india-kerala (accessed on 15 August 2017).
- Tayyebi, A.; Meehan, T.D.; Dischler, J.; Radloff, G.; Ferris, M.; Gratton, C. SmartScape™: A web-based decision support system for assessing the tradeoffs among multiple ecosystem services under crop-change scenarios. Comput. Electron. Agric. 2016, 121, 108–121. [Google Scholar] [CrossRef]
- Agarwal, V. New App Promises to Tell Indian Farmers When to Sow Crops. Available online: https://blogs.wsj.com/indiarealtime/2016/06/17/new-app-promises-to-tell-indian-farmers-when-to-sow-crops/ (accessed on 17 June 2016).
- Aher, P.D.; Adinarayana, J.; Gorantiwar, S.D.; Sawant, S.A. Information System for Integrated Watershed Management Using Remote Sensing and GIS. Remote Sens. Appl. Environ. Res. 2014, 17–34. [Google Scholar] [CrossRef]
- Aggarwal, P.K.; Baethegan, W.E.; Cooper, P.; Gommes, R.; Lee, B.; Meinkef, H.; Rathoreg, L.S.; Sivakumarh, M.V.K. Managing Climatic Risks to Combat Land Degradation and Enhance Food security: Key Information Needs. Procedia Environ. Sci. 2010, 1, 305–312. [Google Scholar] [CrossRef] [Green Version]
- Fourati, M.A.; Chebbi, W.; Kamoun, A. Development of a Web-based weather station for irrigation scheduling. In Proceedings of the 2014 Third IEEE Colloquium in Information Science and Technology, Tetouan, Morocco, 20–22 October 2014; pp. 37–41. [Google Scholar] [CrossRef]
- Lillesand, T.; Kiefer, R.W.; Chipman, J. Remote Sensing and Image Interpretation; John Wiley and Sons: New York, NY, USA, 2014. [Google Scholar]
- Duncan, J.M.; Haworth, B.; Biggs, E.; Boruff, B.; Wales, N.; Bruce, E. Managing multifunctional landscapes: Local insights from a Pacific Island country context. J. Environ. Manag. in review.
- Bojovic, D.; Bonzanigo, L.; Giupponi, C.; Maziotis, A. Online participation in climate change adaptation: A case study of agricultural adaptation measures in Northern Italy. J. Environ. Manag. 2015, 157, 8–19. [Google Scholar] [CrossRef]
- Haworth, B.T. Implications of Volunteered Geographic Information for Disaster Management and GIScience: A More Complex World of Volunteered Geography. Ann. Am. Assoc. Geogr. 2018, 108, 226–240. [Google Scholar] [CrossRef]
- Haworth, B.; Whittaker, J.; Bruce, E. Assessing the application and value of participatory mapping for community bushfire preparation. Appl. Geogr. 2016, 76, 115–127. [Google Scholar] [CrossRef]
- Wheeler, D. Quantifying Vulnerability to Climate Change: Implications for Adaptation Assistance; Center for Global Development Working Paper No. 240; Center for Global Development: Washington, DC, USA, 2011. [Google Scholar]
- Kreft, S.; Eckstein, D.; Dorsch, L.; Fischer, L. Global Climate Risk Index 2016: Who Suffers Most from Extreme Weather Events? Weather-Related Loss Events in 2014 and 1995 to 2014. Germanwatch Nord-Süd Initiative eV. 2015. Available online: https://germanwatch.org/fr/download/13503.pdf (accessed on 15 August 2017).
- Notre Dame Global Adaptation Initiative (NDGAI). Notre Dame Global Adaptation Index. 2017. Available online: http://index.gain.org (accessed on 14 August 2017).
- Internet Usage Statistics. Internet World Stats. N.p., 9 June 2017. Available online: http://www.internetworldstats.com/stats.htm (accessed on 12 June 2017).
- Neis, P.; Zipf, A. Analyzing the contributor activity of a volunteered geographic information project—The case of OpenStreetMap. Int. J. Geo-Inf. 2012, 1, 146–165. [Google Scholar] [CrossRef]
- IFAD. Good Practices in Participatory Mapping; Prepared by Corbett, J.M.; The International Fund for Agricultural Development: Rome, Italy, 2009. [Google Scholar]
- Corbett, J.M.; Keller, C.P. An analytical framework to examine empowerment associated with participatory geographic information systems (PGIS). Cartogr. Int. J. Geogr. Inf. Geovis. 2005, 40, 91–102. [Google Scholar] [CrossRef]
- Corbett, J. “I Don’t Come from Anywhere”: Exploring the Role of the Geoweb and Volunteered Geographic Information in Rediscovering a Sense of Place in a Dispersed Aboriginal Community. In Crowdsourcing Geographic Knowledge: Volunteered Geographic Information (VGI) in Theory and Practice; Sui, D.Z., Elwood, S., Goodchild, M.F., Eds.; Springer: Berlin, Germany, 2013; pp. 223–241. [Google Scholar]
- Mercer, J.; Dominey-Howes, D.; Kelman, I.; Lloyd, K. The potential for combining indigenous and western knowledge in reducing vulnerability to environmental hazards in small island developing states. Environ. Hazards 2007, 7, 245–256. [Google Scholar] [CrossRef]
- Menike, L.; Arachchi, K.K. Adaptation to climate change by smallholder farmers in rural communities: Evidence from Sri Lanka. Procedia Food Sci. 2016, 6, 282–292. [Google Scholar] [CrossRef]
- Jones, L.; Harvey, B.; Cochrane, L.; Cantin, B.; Conway, D.; Cornforth, R.J.; De Souza, K.; Kirbyshire, A. Designing the next generation of climate adaptation research or development. Reg. Environ. Chang. 2018, 18, 297–304. [Google Scholar] [CrossRef]
- World Economic Forum (WEF). The Global Risks Report 2017, 12th ed.; World Economic Forum: Geneva, Switzerland, 2017; Available online: http://reports.weforum.org/global-risks-2017/ (accessed on 14 August 2017).
- Harvey, C.A.; Saborio-Rodriguez, M.; Martinez-Rodriguez, M.R.; Viguera, B.; Chain-Guadarrama, A.; Vignola, R.; Alpizar, F. Climate change impacts and adaptation among smallholder farmers in Central America. Agric. Food Secur. 2018, 7, 57. [Google Scholar] [CrossRef]
- Abdul-Razak, M.; Kruse, S. The adaptive capacity of smallholder farmers to climate change in Northern Region of Ghana. Clim. Risk Manag. 2017, 17, 104–122. [Google Scholar] [CrossRef]
- Martinez-Baron, D.; Orjuela, G.; Renzoni, G.; Loboguerrero Rodriguez, A.M.; Prager, S.D. Small-scale farmers in a 1.5 °C future: The importance of local social dynamics as an enabling factor for implementation and scaling of climate-smart agriculture. Curr. Opin. Environ. Sustain. 2018, 31, 112–119. [Google Scholar] [CrossRef]
- Biggs, E.M.; Bruce, E.; Boruff, B.; Duncan, J.M.A.; Horsley, J.; Pauli, N.; McNeil, K.; Neef, A.; Van Ogtrop, F.; Curnow, J.; et al. Sustainable development and the water-energy-food nexus: A perspective on livelihoods. Environ. Sci. Policy 2015, 54, 389–397. [Google Scholar] [CrossRef]
- Kremen, C.; Merenlender, A.M. Landscapes that work for biodiversity and people. Science 2018, 362, eaau6020. [Google Scholar] [CrossRef] [PubMed]
Initiative | Description | Targeted Country or Region | Source |
---|---|---|---|
Agriculture Monitoring System | Agriculture monitoring system and technologies for collecting, analysing, and disseminating information. Includes satellite remote sensing, GIS, and mobile GPS. Provides a knowledge base for government, NGOs, rural communities and other stakeholders that will aid sustainable land use and agriculture. | Afghanistan | [58] |
Airtel Kilimo | Mobile phone and SMS advisory service. Dissemination of information related to crops, weather and market prices for improved farmer livelihood security. | Kenya | [59] |
Avaaj Otalo | Top-down mobile phone advisory service. Delivery of weather, crop, fertiliser and other agriculture information to farmers. Addresses shortcomings of the extension system. | India | [60] |
Climate Wizard Tool | Web-based system for climate change data analysis and mapping. Provides practical information for local and regional agriculture managers. Facilitates advanced statistical analyses for more technical users. | Global | [61] |
CROPROTECT | Internet and smartphone application utilising GIS and Google Earth. Knowledge exchange system for farmers to acquire and share information relating to pest, weed and disease management. | United Kingdom | [62] |
Digital Green | Participatory videos (local languages) used to involve local communities in sharing scientific agriculture information and local knowledge to improve livelihoods through better and more adaptive farming practices. | India, Ghana, Ethiopia | [53,63] |
Farmer Decision Support System (FDSS) | Advisory information for registered farmers via SMS to assist farming decisions e.g., when and how to plant, harvest, fertilise and manage crops. 7-day weather forecasts also provided. | Philippines | [64] |
Farmforce | SMS and smartphone application to link farmers with other actors in the agro-value chain to reduce transaction costs, aid compliance with food standards, and increase information exchange. | Asia, Africa, Latin America | [65] |
Geospatial Information for Rice Crop Monitoring (GIRCM) | Agriculture information derived from image classification and rice crop area estimation to enhance food security. Still in proposal stage. | Afghanistan | [66] |
Indian Farmers Fertiliser Cooperative (IFFCO) Kisan Agriculture App | Smartphone application to provide crop information in various formats for enhanced decision making. Aimed at farmers who are receptive to new technologies and business approaches. | India | [67] |
Information Technology and Indigenous Knowledge with Intelligence (ITIKI) | Early warning system that integrates information from sensor networks and local knowledge on droughts. Communication using SMS, mobile phone calls, website posts, digital billboards and radio broadcasts to disseminate forecast information to farmers. | Kenya, Sub-Saharan Africa | [68] |
iska | GPS-located weather forecasts (various time intervals) distributed via SMS to farmers to improve decision making and reduce weather-related crop losses. | West Africa | [69,70] |
Jayalaxmi Agro Tech | Crop-specific smartphone applications for access to agriculture, horticulture and animal husbandry information (English and regional languages). | India | [71] |
LandCaRe DSS | Spatial simulation modelling to produce information for stakeholders and farmers involved in decision making related to land management and long-term impacts of climate change at regional and farm scales. | Germany | [72] |
Mobile geospatial information for African farmers (MGIAF) | Mobile phone alerts regarding purchasing of drought-tolerant crops for farmers in remote regions. GIS maps for extension officers and community development workers for information dissemination to farmers. | Kenya | [73] |
Mobile market information service (MMIS) | SMS request service for rural farmers to receive information on market information (e.g., product prices) to improve selling practices and decision making. | Papua New Guinea | [74] |
Mobile soil information for African farmers (MSIAF) | Web-mapping platform for providing soil information to farmers and government workers. Accessed via the internet or mobile phone. | Kenya | [73] |
(M)obile Solutions | Mobile phone voice and SMS messages (Hindi or a local language) sent to farmers. Contain information relating to weather, pests, seed varieties, climate change and climate-smart technologies. Provides recommended actions. Option for farmers to provide feedback to inform future messaging. | India | [27] |
Participatory Mapping Disaster Risk Reduction Local Knowledge (PMDRRLK) | Participatory approaches and co-produced mapping to improve local resilience to climate change related hazards and increase the use of local environmental knowledge. | Switzerland | [75] |
Plantwise Knowledge Bank | Online and smartphone-based knowledge bank with pest identification tools and factsheets on plant health to aid community farming. | Global | [62] |
Radio Monsoon | National meteorological information and local knowledge for weather forecasts disseminated to fishermen via social media and the internet, landline and mobile phones, and loudspeakers positioned in fishing communities. | India | [76] |
SmartScape | Internet and GIS tool to allow users to experiment with policy options, predict cropping system changes, and compare cropping scenarios. Produces information to be shared with stakeholders, such as policymakers, community agriculture groups, or non-government organisations. | United States of America | [77] |
Sowing Application | Smartphone application and SMS used to advise registered farmers best times for sowing seeds based on soil health indicators and rainfall and weather information. Alerts issued for extreme weather conditions that may damage crops or impact farmers. | India | [78] |
Tigo Kilimo | Mobile phone dissemination of information on weather, crops and markets for enhanced decision making to improve food security, livelihoods and household income for farmers. | Tanzania | [51] |
Watershed Management Information System (WATMIS) | Web-based information and decision support system integrating soil, vegetation, climate and other environment information to assist agriculturalists, resource managers and the rural extension community in managing water scarcity. | India | [79] |
World AgroMeteorological Information Service (WAMIS) | Web-server for disseminating agrometeorological products and information bulletins. Provides knowledge and training to large numbers of agriculture stakeholders cost effectively via the internet. | Global | [80] |
Wireless Sensor Network—Decision Support System (WSN-DSS) | Wireless sensor network and web-based decision support system for irrigation scheduling. Supports farmers in restructuring agricultural land to address issues of food security and inefficient farming. | Tunisia | [81] |
Factors Promoting Success | Factors Limiting Success | |
---|---|---|
Farmer capacity | Affordability to farmers | Participation capacity (exclusion through gender, costs, digital divide) |
Available languages | Limited languages | |
Information alone often not enough for meaningful change | ||
Approach | Partnerships with existing community groups | Methods for incorporating community knowledge into GIS |
User collaboration/sharing | Purely top-down approach—lack of interactivity | |
Farmers involved in design | User registration required | |
Technological | High quality, locally-relevant information | Acquisition and sourcing of suitable and quality information/data |
Low tech and user friendly—ease of use | Availability and capacity of telecommunications infrastructure | |
Allows participant feedback—interactivity functionality | Personal and community information security | |
Organisational | Organisational trust | Low user retention |
Potential for expansion—agile service | (In)ability to reach target users | |
Marketing and endorsements | ||
Clear business model, including funding | Funding of initiatives |
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Share and Cite
Haworth, B.T.; Biggs, E.; Duncan, J.; Wales, N.; Boruff, B.; Bruce, E. Geographic Information and Communication Technologies for Supporting Smallholder Agriculture and Climate Resilience. Climate 2018, 6, 97. https://doi.org/10.3390/cli6040097
Haworth BT, Biggs E, Duncan J, Wales N, Boruff B, Bruce E. Geographic Information and Communication Technologies for Supporting Smallholder Agriculture and Climate Resilience. Climate. 2018; 6(4):97. https://doi.org/10.3390/cli6040097
Chicago/Turabian StyleHaworth, Billy Tusker, Eloise Biggs, John Duncan, Nathan Wales, Bryan Boruff, and Eleanor Bruce. 2018. "Geographic Information and Communication Technologies for Supporting Smallholder Agriculture and Climate Resilience" Climate 6, no. 4: 97. https://doi.org/10.3390/cli6040097
APA StyleHaworth, B. T., Biggs, E., Duncan, J., Wales, N., Boruff, B., & Bruce, E. (2018). Geographic Information and Communication Technologies for Supporting Smallholder Agriculture and Climate Resilience. Climate, 6(4), 97. https://doi.org/10.3390/cli6040097